The major problem addressed in this proposal is the development and evaluation of an automated noninvasive approach to discriminate different normal and pathological tissue types using machine learning algorithms; previous applications of machine learning have been based on features of the backscattered ultrasound that are essentially energy based. Our approach will be based on extracting features from images whose pixels are determined by the entropy contained in segments of the backscattered ultrasound. The unique attributes of entropy imaging suggest that the automated analysis we propose would be particularly robust for discrimination of deep tissues in a clinical environment.